The significance of changes in serial test results must be properly assessed, for example during clinical trials which tend to be time consuming and expensive. Because of weak signals from biomarker data, critical data obtained during phase I clinical trials can be difficult to interpret. Accurate interpretation of these signals is of great interest, because significant resources are often spent on compounds that ultimately fail in phase III clinical trials.
There is a need for methods and systems that allow clinical laboratory data to be quantitated more effectively and reliably.